AI FOR REGIONAL ART MAPPING AND PRESERVATION - Gupta, Peeyush Kumar; Shrivastav, Amit Kumar; Modi, Priya; Khalique, Fehmina; Bhardwaj, Nishant; Singh, Archana; Anerao, Prashant (ShodhKosh: Journal of Visual and Performing Arts, 2025)
Artificial intelligence has proven to be a paradigm shift in preservation of cultural heritage and has made it possible to digitize vast portions of heritage, classify intelligently and semantically interconnect regional art forms. The paper introduces a full-fledged AI-based regional art mapping and preservation framework that incorporates various forms of multimodal data visual, textual, and geospatial data in an integrated cultural knowledge framework. The architecture has five layers, including data acquisition, AI analytics, knowledge graph integration, visualization interfaces and ethical governance. The implementation revolves around the Regional Art Knowledge Graph (RAKG) and Cultural Atlas Interface that establishes a semantic and interactive environment of exploring artistic relationships in terms of regions, styles, and time. Technical accuracy (A 1 = 92.3, F1 = 0.91, SSI = 0.84) and cultural authenticity (CAS = 8.7/10, RDI = 0.82) are good. Transparency and contextual fidelity are guaranteed by the presence of explainable AI systems and community engagement systems. The fusion of computational intelligence and human creativity allows the presented system to transform heritage preservation to a dynamic process that is participatory and ties the local traditions to a global digital future.